Causal Evidence from a Post-Rationing Reform
04 June, 2025
It’s a big problem
Limited credible causal evidence
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A lot of evidence for a detrimental effect of alcohol on health
Difficult to identify causal …
Natural experiments, a fix?
All cause mortality (1968-2023)
Motor vehicle accidents (1985-2023)
Sales in Liters of alcohol (1978-2008)
900 municipalities in 1968, 288 in 1996 (Source: REGINA, SCB)
Mortality data aggregated to 1995 municipal borders
INSERT DCDH AND CS PLOT HERE (MAKE A NEW ONE!) + Or maybe skip as this reveals the result? Maybe add at the end, after robustness?
The population equation of interest is
\[\begin{equation} Y_{mt} = \gamma_m + \lambda_t + \beta_{mt} \text{store}_{mt} + \epsilon_{mt}\, , \label{eq:pop-eq-of-interest} \end{equation}\]
1st store test uses municipalities with no store a the control group
2nd store test uses municipalities with only one store as control group
The 1st store test (mechanically) confirms that the treatment is well-defined, i.e. municipalities see positive in-store sales compared to municipalities without a store.
The 2nd store test is more interesting. It shows that municipalities that open a 2nd store increase their sales with about 25%.
Caveats:
If we multiply the coefficient on total alcohol sales from the ‘Saturday’ experiment by the number of days Systembolaget is open (today), we get \(0.035 \times 6 = 0.21\), compared to the \(0.25\) from the 2nd store test (column 5).
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Describe the test and treatment df